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    "language_info": {
      "name": "python"
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  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Rede LSTM para previsão de Fechamento de uma Ação\n"
      ],
      "metadata": {
        "id": "_D1sQZY1f41e"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Importando Bibliotecas necessarias para Deep Learning e Mercado Financeiro"
      ],
      "metadata": {
        "id": "fA7wEvxPgwRd"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {
        "id": "MFGuEl4oBcFj"
      },
      "outputs": [],
      "source": [
        "import yfinance as yf\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "import matplotlib.pyplot as plt\n",
        "import tensorflow as tf\n",
        "from tensorflow.keras.models import Sequential\n",
        "from tensorflow.keras.layers import LSTM, Dense, Dropout\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Download dos Dados e visualização do dataset"
      ],
      "metadata": {
        "id": "HblN_WM_hDFT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Baixar dados\n",
        "ticker = 'AAPL'\n",
        "df = yf.download(ticker, start=\"2018-01-01\", end=\"2023-12-31\")\n",
        "df = df[['Open', 'High', 'Low', 'Close', 'Volume']]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9XezksJVhCgE",
        "outputId": "fd4efbb0-2465-4525-e439-496c0e1da74c"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r[*********************100%***********************]  1 of 1 completed\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "id": "e5eBRagyBpcs",
        "outputId": "499339d1-851c-41dd-8d38-afef9357b321"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Price            Open       High        Low      Close     Volume\n",
              "Ticker           AAPL       AAPL       AAPL       AAPL       AAPL\n",
              "Date                                                             \n",
              "2018-01-02  39.933986  40.436212  39.722768  40.426823  102223600\n",
              "2018-01-03  40.490187  40.964251  40.356418  40.419781  118071600\n",
              "2018-01-04  40.492539  40.710798  40.384586  40.607536   89738400\n",
              "2018-01-05  40.703747  41.156687  40.612220  41.069855   94640000\n",
              "2018-01-08  40.917320  41.213022  40.818749  40.917320   82271200"
            ],
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              "      <th>AAPL</th>\n",
              "      <th>AAPL</th>\n",
              "      <th>AAPL</th>\n",
              "      <th>AAPL</th>\n",
              "      <th>AAPL</th>\n",
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              "      <th>Date</th>\n",
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              "    <tr>\n",
              "      <th>2018-01-02</th>\n",
              "      <td>39.933986</td>\n",
              "      <td>40.436212</td>\n",
              "      <td>39.722768</td>\n",
              "      <td>40.426823</td>\n",
              "      <td>102223600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-03</th>\n",
              "      <td>40.490187</td>\n",
              "      <td>40.964251</td>\n",
              "      <td>40.356418</td>\n",
              "      <td>40.419781</td>\n",
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              "    <tr>\n",
              "      <th>2018-01-04</th>\n",
              "      <td>40.492539</td>\n",
              "      <td>40.710798</td>\n",
              "      <td>40.384586</td>\n",
              "      <td>40.607536</td>\n",
              "      <td>89738400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-05</th>\n",
              "      <td>40.703747</td>\n",
              "      <td>41.156687</td>\n",
              "      <td>40.612220</td>\n",
              "      <td>41.069855</td>\n",
              "      <td>94640000</td>\n",
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              "    <tr>\n",
              "      <th>2018-01-08</th>\n",
              "      <td>40.917320</td>\n",
              "      <td>41.213022</td>\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 1509,\n  \"fields\": [\n    {\n      \"column\": [\n        \"Date\",\n        \"\"\n      ],\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2018-01-02 00:00:00\",\n        \"max\": \"2023-12-29 00:00:00\",\n        \"num_unique_values\": 1509,\n        \"samples\": [\n          \"2020-04-21 00:00:00\",\n          \"2022-07-22 00:00:00\",\n          \"2019-07-11 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"Open\",\n        \"AAPL\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 51.00027093346702,\n        \"min\": 34.297229415515666,\n        \"max\": 196.58041195784497,\n        \"num_unique_values\": 1509,\n        \"samples\": [\n          66.95955078291355,\n          152.93639744167695,\n          48.825147274762735\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"High\",\n        \"AAPL\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 51.51613168434412,\n        \"min\": 34.71171315877286,\n        \"max\": 198.16877097511053,\n        \"num_unique_values\": 1509,\n        \"samples\": [\n          67.19464143835056,\n          153.8123437761435,\n          49.084511049744144\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"Low\",\n        \"AAPL\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 50.51268274006018,\n        \"min\": 33.825578007512746,\n        \"max\": 195.56783406915136,\n        \"num_unique_values\": 1509,\n        \"samples\": [\n          64.32993033303205,\n          150.98766576840873,\n          48.4409074952628\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"Close\",\n        \"AAPL\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 51.04133116704222,\n        \"min\": 33.8708381652832,\n        \"max\": 196.6697540283203,\n        \"num_unique_values\": 1493,\n        \"samples\": [\n          146.2874755859375,\n          142.95521545410156,\n          173.42364501953125\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": [\n        \"Volume\",\n        \"AAPL\"\n      ],\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 55133307,\n        \"min\": 24048300,\n        \"max\": 426510000,\n        \"num_unique_values\": 1505,\n        \"samples\": [\n          157618800,\n          137827700,\n          98217600\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8pi6PfGPBoMI",
        "outputId": "32e9647f-e16d-45b5-c783-048bd6f54a00"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "DatetimeIndex: 1509 entries, 2018-01-02 to 2023-12-29\n",
            "Data columns (total 5 columns):\n",
            " #   Column          Non-Null Count  Dtype  \n",
            "---  ------          --------------  -----  \n",
            " 0   (Open, AAPL)    1509 non-null   float64\n",
            " 1   (High, AAPL)    1509 non-null   float64\n",
            " 2   (Low, AAPL)     1509 non-null   float64\n",
            " 3   (Close, AAPL)   1509 non-null   float64\n",
            " 4   (Volume, AAPL)  1509 non-null   int64  \n",
            "dtypes: float64(4), int64(1)\n",
            "memory usage: 70.7 KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Normalização dos dados"
      ],
      "metadata": {
        "id": "1tL1fvkzhWue"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Escalador geral para features\n",
        "scaler_full = MinMaxScaler()\n",
        "df_scaled = pd.DataFrame(scaler_full.fit_transform(df), columns=df.columns, index=df.index)\n",
        "\n",
        "# Escalador dedicado para o target\n",
        "scaler_target = MinMaxScaler()\n",
        "df_scaled['Close'] = scaler_target.fit_transform(df[['Close']])\n"
      ],
      "metadata": {
        "id": "mtZCGbnMBw6M"
      },
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Criando sequencias temporais multivariaveis"
      ],
      "metadata": {
        "id": "etc6Z43Ahj3H"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def create_multivariate_sequences(dataframe, window_size=60, target_column='Close'):\n",
        "    data = dataframe.values\n",
        "    target_index = dataframe.columns.get_loc(target_column)\n",
        "    X, y = [], []\n",
        "    for i in range(window_size, len(data)):\n",
        "        X.append(data[i - window_size:i])\n",
        "        y.append(data[i, target_index])\n",
        "    return np.array(X), np.array(y)\n",
        "\n"
      ],
      "metadata": {
        "id": "BR5agEs9B01n"
      },
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "window_size = 60\n",
        "X, y = create_multivariate_sequences(df_scaled, window_size=window_size, target_column='Close')\n"
      ],
      "metadata": {
        "id": "hDYy7kHnhhyL"
      },
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Dividndo os dados em Treino e Teste"
      ],
      "metadata": {
        "id": "B9Vs4ieZhtGy"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Dividir treino/teste\n",
        "split = int(len(X) * 0.8)\n",
        "X_train, X_test = X[:split], X[split:]\n",
        "y_train, y_test = y[:split], y[split:]"
      ],
      "metadata": {
        "id": "duv51zOFhrEr"
      },
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Criando modelo LSTM Muti variaveis"
      ],
      "metadata": {
        "id": "NEOnTqbhh0qX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "model = Sequential([\n",
        "    LSTM(128, return_sequences=True, input_shape=(X_train.shape[1], X_train.shape[2])),\n",
        "    Dropout(0.2),\n",
        "    LSTM(64),\n",
        "    Dropout(0.2),\n",
        "    Dense(1)\n",
        "])\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "keeUM0etCMMS",
        "outputId": "a76b1970-d960-45ed-cf3c-78d62cd49473"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.11/dist-packages/keras/src/layers/rnn/rnn.py:200: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n",
            "  super().__init__(**kwargs)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.summary()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298
        },
        "id": "NveiMTLkf1ND",
        "outputId": "c5ce02e5-e0a9-4c25-cd90-380fbbb9500c"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[1mModel: \"sequential_3\"\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_3\"</span>\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
              "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
              "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
              "│ lstm_6 (\u001b[38;5;33mLSTM\u001b[0m)                   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m60\u001b[0m, \u001b[38;5;34m128\u001b[0m)        │        \u001b[38;5;34m68,608\u001b[0m │\n",
              "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
              "│ dropout_6 (\u001b[38;5;33mDropout\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m60\u001b[0m, \u001b[38;5;34m128\u001b[0m)        │             \u001b[38;5;34m0\u001b[0m │\n",
              "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
              "│ lstm_7 (\u001b[38;5;33mLSTM\u001b[0m)                   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m)             │        \u001b[38;5;34m49,408\u001b[0m │\n",
              "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
              "│ dropout_7 (\u001b[38;5;33mDropout\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m)             │             \u001b[38;5;34m0\u001b[0m │\n",
              "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
              "│ dense_3 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m)              │            \u001b[38;5;34m65\u001b[0m │\n",
              "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
              "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
              "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
              "│ lstm_6 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>)                   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">60</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)        │        <span style=\"color: #00af00; text-decoration-color: #00af00\">68,608</span> │\n",
              "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
              "│ dropout_6 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">60</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)        │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
              "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
              "│ lstm_7 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>)                   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)             │        <span style=\"color: #00af00; text-decoration-color: #00af00\">49,408</span> │\n",
              "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
              "│ dropout_7 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)             │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
              "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
              "│ dense_3 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">1</span>)              │            <span style=\"color: #00af00; text-decoration-color: #00af00\">65</span> │\n",
              "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m118,081\u001b[0m (461.25 KB)\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">118,081</span> (461.25 KB)\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m118,081\u001b[0m (461.25 KB)\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">118,081</span> (461.25 KB)\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Compilando e Treinando o Modelo"
      ],
      "metadata": {
        "id": "I_jT_SwXlsVN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "model.compile(optimizer='adam', loss='mean_squared_error')\n",
        "model.fit(X_train, y_train, epochs=30, batch_size=32, verbose=1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LYf1haoPh804",
        "outputId": "0b431c54-1b4b-426d-ab8a-c73b12515391"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 102ms/step - loss: 0.0346\n",
            "Epoch 2/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 97ms/step - loss: 0.0025\n",
            "Epoch 3/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 96ms/step - loss: 0.0022\n",
            "Epoch 4/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 111ms/step - loss: 0.0022\n",
            "Epoch 5/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 96ms/step - loss: 0.0021\n",
            "Epoch 6/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 98ms/step - loss: 0.0024\n",
            "Epoch 7/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 155ms/step - loss: 0.0024\n",
            "Epoch 8/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 112ms/step - loss: 0.0020\n",
            "Epoch 9/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 97ms/step - loss: 0.0019\n",
            "Epoch 10/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 97ms/step - loss: 0.0021\n",
            "Epoch 11/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 134ms/step - loss: 0.0017\n",
            "Epoch 12/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 98ms/step - loss: 0.0023\n",
            "Epoch 13/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 97ms/step - loss: 0.0022\n",
            "Epoch 14/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 116ms/step - loss: 0.0018\n",
            "Epoch 15/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 98ms/step - loss: 0.0017\n",
            "Epoch 16/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 137ms/step - loss: 0.0017\n",
            "Epoch 17/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 98ms/step - loss: 0.0017\n",
            "Epoch 18/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 101ms/step - loss: 0.0015\n",
            "Epoch 19/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 142ms/step - loss: 0.0015\n",
            "Epoch 20/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 98ms/step - loss: 0.0018\n",
            "Epoch 21/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 99ms/step - loss: 0.0020\n",
            "Epoch 22/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 140ms/step - loss: 0.0018\n",
            "Epoch 23/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 98ms/step - loss: 0.0019\n",
            "Epoch 24/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 138ms/step - loss: 0.0016\n",
            "Epoch 25/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 97ms/step - loss: 0.0015\n",
            "Epoch 26/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 99ms/step - loss: 0.0015\n",
            "Epoch 27/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 139ms/step - loss: 0.0015\n",
            "Epoch 28/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 98ms/step - loss: 0.0014\n",
            "Epoch 29/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 138ms/step - loss: 0.0015\n",
            "Epoch 30/30\n",
            "\u001b[1m37/37\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 98ms/step - loss: 0.0015\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.src.callbacks.history.History at 0x7cfe46c4f090>"
            ]
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Plot das Previsões"
      ],
      "metadata": {
        "id": "Q9rdU-yZlzPH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Prever\n",
        "y_pred_scaled = model.predict(X_test)\n",
        "y_pred = scaler_target.inverse_transform(y_pred_scaled)\n",
        "y_test_rescaled = scaler_target.inverse_transform(y_test.reshape(-1, 1))\n",
        "\n",
        "# Plotar\n",
        "plt.figure(figsize=(12, 6))\n",
        "plt.plot(y_test_rescaled, label='Real')\n",
        "plt.plot(y_pred, label='Previsto')\n",
        "plt.title(f'Previsão com LSTM Multivariada - {ticker}')\n",
        "plt.xlabel('Dias')\n",
        "plt.ylabel('Preço de Fechamento (US$)')\n",
        "plt.legend()\n",
        "plt.grid(True)\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 582
        },
        "id": "79sGLDJ-CbBM",
        "outputId": "67d4a4fe-ddcb-4c27-e571-f04417605d88"
      },
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1m10/10\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 66ms/step\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Prever na Realidade"
      ],
      "metadata": {
        "id": "S71nHyVae_yP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def prever_proximo_valor_multivariado(df_original, model, window_size, scaler_full, scaler_target):\n",
        "    df_recent = df_original[-window_size:]\n",
        "    df_scaled_recent = scaler_full.transform(df_recent)\n",
        "    entrada = df_scaled_recent.reshape((1, window_size, df_scaled_recent.shape[1]))\n",
        "\n",
        "    pred_scaled = model.predict(entrada)\n",
        "\n",
        "    return scaler_target.inverse_transform(pred_scaled)[0, 0]\n"
      ],
      "metadata": {
        "id": "LnDhZ_rIDrue"
      },
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "previsao_proximo_dia = prever_proximo_valor_multivariado(df, model, window_size, scaler_full, scaler_target)\n",
        "print(f\"📅 Previsão para o próximo dia: US$ {previsao_proximo_dia:.2f}\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "g11U-YjYfF0e",
        "outputId": "3d3e0ebb-6164-4eb8-b3cd-d8f59a5ffa75"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 64ms/step\n",
            "📅 Previsão para o próximo dia: US$ 191.18\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay\n",
        "\n",
        "# 1. Converter previsões e valores reais em arrays unidimensionais\n",
        "y_pred_flat = y_pred.flatten()\n",
        "y_real_flat = y_test_rescaled.flatten()\n",
        "\n",
        "# 2. Calcular direções (1 = subida, 0 = descida ou igual)\n",
        "def calcular_direcao(series):\n",
        "    return (np.diff(series) > 0).astype(int)\n",
        "\n",
        "direcao_real = calcular_direcao(y_real_flat)\n",
        "direcao_pred = calcular_direcao(y_pred_flat)\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "iBy3kXKVl5q3"
      },
      "execution_count": 40,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# 3. Calcular matriz de confusão\n",
        "cm = confusion_matrix(direcao_real, direcao_pred)\n",
        "disp = ConfusionMatrixDisplay(confusion_matrix=cm, display_labels=[\"Queda\", \"Subida\"])\n",
        "\n",
        "# 4. Exibir\n",
        "disp.plot(cmap='Blues')\n",
        "plt.title(\"Matriz de Confusão - Direção de Tendência\")\n",
        "plt.xlabel(\"Predito\")\n",
        "plt.ylabel(\"Real\")\n",
        "plt.grid(False)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "P8vRdD-VnqIk",
        "outputId": "8058a26a-9f3a-4353-f11b-41fab5f86f12"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Acurácia de direção: % de vezes em que a predição acertou a direção do movimento\n",
        "acertos = np.sum(direcao_real == direcao_pred)\n",
        "total = len(direcao_real)\n",
        "acuracia_direcao = acertos / total\n",
        "\n",
        "print(f\"✅ Acurácia de direção: {acuracia_direcao * 100:.2f}% ({acertos}/{total})\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YddfGILfodtU",
        "outputId": "b4ee2e5e-da80-4834-f531-bc37a3c57578"
      },
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "✅ Acurácia de direção: 50.52% (146/289)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Na teoria, temoos um modelo vencedor -> Accuracia > 50%"
      ],
      "metadata": {
        "id": "G2uZew7SpJ5-"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## ✅ 2. **Gráfico com Setas de Tendência**\n",
        "\n",
        "As **tendências reais** e **preditas** em um mesmo gráfico. Usaremos setas verticais com cores:\n",
        "\n",
        "* 🔵 Azul para tendência **real**\n",
        "* 🔴 Vermelho para tendência **predita**\n",
        "\n"
      ],
      "metadata": {
        "id": "i9Bpl0aZpbQq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(16, 5))\n",
        "dias = np.arange(len(direcao_real))\n",
        "\n",
        "# Plot base da ação real\n",
        "plt.plot(y_real_flat[1:], label='Preço Real', color='black', alpha=0.3)\n",
        "\n",
        "# Setas de tendência real\n",
        "for i, direcao in enumerate(direcao_real):\n",
        "    cor = 'blue' if direcao == 1 else 'blue'\n",
        "    dy = 1.0 if direcao == 1 else -1.0\n",
        "    plt.arrow(i, y_real_flat[i+1], 0, dy, color=cor, head_width=0.5, head_length=0.5, alpha=0.3)\n",
        "\n",
        "# Setas de tendência predita\n",
        "for i, direcao in enumerate(direcao_pred):\n",
        "    cor = 'red' if direcao == 1 else 'red'\n",
        "    dy = 1.0 if direcao == 1 else -1.0\n",
        "    plt.arrow(i, y_pred_flat[i+1], 0, dy, color=cor, head_width=0.5, head_length=0.5, alpha=0.3)\n",
        "\n",
        "plt.title(\"Setas de Tendência – Real (Azul) vs Predita (Vermelha)\")\n",
        "plt.xlabel(\"Dias\")\n",
        "plt.ylabel(\"Preço\")\n",
        "plt.grid(True)\n",
        "plt.legend([\"Preço Real\"])\n",
        "plt.tight_layout()\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "2hiKzg0soke7",
        "outputId": "5e44e061-ef65-4a2a-960b-ed1e57f024b0"
      },
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1600x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}